As a technology for identifying an object in image data, for example, there has been a technology in which a part-to-part arrangement in an object is evaluated to estimate an attitude of the object. This technology is based on the assumption that an object to be identified exists in an image, and thus, suits detection for details of the attitude of the object, but does not suit detection of presence or absence of the object, disadvantageously resulting in inability to identify the object with high accuracy.
Additionally, there has been a technology in which an entire area is detected and thereafter, each individual local area in the detected area is searched for a feature vector. However, this technology cannot accurately detect the entire area if the individual local area varies, disadvantageously resulting in deterioration in identification accuracy for the object.
Moreover, there has been a technology in which a likelihood is calculated for each detected feature point by comparison with a codebook, and the calculated likelihoods are collected to identify the object. However, this technology uses a detection result of the feature point, which varies the identification accuracy of the feature point depending on detection accuracy, disadvantageously leading to unsteady identification accuracy.